Vertebrate conserved non coding DNA regions have a high persistence length and a short persistence time.

BACKGROUND: The comparison of complete genomes has revealed surprisingly large numbers of conserved non-protein-coding (CNC) DNA regions. However, the biological function of CNC remains elusive. CNC differ in two aspects from conserved protein-coding regions. They are not conserved across phylum boundaries, and they do not contain readily detectable sub-domains. Here we characterize the persistence length and time of CNC and conserved protein-coding regions in the vertebrate and insect lineages. RESULTS: The persistence length is the length of a genome region over which a certain level of sequence identity is consistently maintained. The persistence time is the evolutionary period during which a conserved region evolves under the same selective constraints.Our main findings are: (i) Insect genomes contain 1.60 times less conserved information than vertebrates; (ii) Vertebrate CNC have a higher persistence length than conserved coding regions or insect CNC; (iii) CNC have shorter persistence times as compared to conserved coding regions in both lineages. CONCLUSION: Higher persistence length of vertebrate CNC indicates that the conserved information in vertebrates and insects is organized in functional elements of different lengths. These findings might be related to the higher morphological complexity of vertebrates and give clues about the structure of active CNC elements.Shorter persistence time might explain the previously puzzling observations of highly conserved CNC within each phylum, and of a lack of conservation between phyla. It suggests that CNC divergence might be a key factor in vertebrate evolution. Further evolutionary studies will help to relate individual CNC to specific developmental processes.

Predicting reptile distributions at the mesoscale: relation to climate and topography

Aim To explore the respective power of climate and topography to predict the distribution of reptiles in Switzerland, hence at a mesoscale level. A more detailed knowledge of these relationships, in combination with maps of the potential distribution derived from the models, is a valuable contribution to the design of conservation strategies. Location All of Switzerland. Methods Generalized linear models are used to derive predictive habitat distribution models from eco-geographical predictors in a geographical information system, using species data from a field survey conducted between 1980 and 1999. Results The maximum amount of deviance explained by climatic models is 65%, and 50% by topographical models. Low values were obtained with both sets of predictors for three species that are widely distributed in all parts of the country (Anguis fragilis , Coronella austriaca , and Natrix natrix), a result that suggests that including other important predictors, such as resources, should improve the models in further studies. With respect to topographical predictors, low values were also obtained for two species where we anticipated a strong response to aspect and slope, Podarcis muralis and Vipera aspis . Main conclusions Overall, both models and maps derived from climatic predictors more closely match the actual reptile distributions than those based on topography. These results suggest that the distributional limits of reptile species with a restricted range in Switzerland are largely set by climatic, predominantly temperature-related, factors.

Amniotic fluid insulin-like growth factor binding protein 3 concentration as early indicator of fetal growth restriction.

OBJECTIVE: Insulin-like growth factor-I (IGF-I) is an important regulator of fetal growth and its bioavailability depends on insulin-like growth factor binding proteins (IGFBPs). Genes coding for IGF-I and IGFBP3 are polymorphic. We hypothesized that either amniotic fluid protein concentration at the beginning of the second trimester or genotype of one of these two genes could be predictive of abnormal fetal growth. STUDY DESIGN: Amniotic fluid samples (14-18 weeks of pregnancy) from 123 patients with appropriate for gestational age (AGA) fetuses, 39 patients with small for gestational age (SGA) fetuses and 34 patients with large for gestational age (LGA) were analyzed. Protein concentrations were evaluated by ELISA and gene polymorphisms by PCR. RESULTS: Amniotic fluid IGFBP3 concentrations were significantly higher in SGA compared to AGA group (P=0.030), and this was even more significant when adjusted to gestational age at the time of amniocentesis and other covariates (ANCOVA analysis: P=0.009). Genotypic distribution of IGF-I variable number of tandem repeats (VNTR) polymorphism was significantly different in SGA compared to AGA group (P=0.029). 19CA/20CA genotype frequency was threefold decreased in SGA compared to AGA group and the risk of SGA occurrence of this genotype was decreased accordingly: OR=0.289, 95%CI=0.1-0.9, P=0.032. Genotype distribution of IGFBP3(A-202C) polymorphism was similar in all three groups. CONCLUSIONS: High IGFBP3 concentrations in amniotic fluid at the beginning of the second trimester are associated with increased risks of SGA while 19CA/20CA genotype at IGF-I VNTR polymorphism is associated with reduced risks of SGA. Neither IGFBP3 concentrations, nor IGF-I/IGFBP3 polymorphisms are associated with modified risks of LGA.

Sensitivity of predictive species distribution models to change in grain size

Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.

Blood glucose level on postoperative day 1 is predictive of adverse outcomes after cardiovascular surgery

AIM: Hyperglycaemia is now a recognized predictive factor of morbidity and mortality after coronary artery bypass grafting (CABG). For this reason, we aimed to evaluate the postoperative management of glucose control in patients undergoing cardiovascular surgery, and to assess the impact of glucose levels on in-hospital mortality and morbidity. METHODS: This was a retrospective study investigating the association between postoperative blood glucose and outcomes, including death, post-surgical complications, and length of stay in the intensive care unit (ICU) and in hospital. RESULTS: A total of 642 consecutive patients were enrolled into the study after cardiovascular surgery (CABG, carotid endarterectomy and bypass in the lower limbs). Patients' mean age was 68+/-10 years, and 74% were male. In-hospital mortality was 5% in diabetic patients vs 2% in non-diabetic patients (OR: 1.66, P=0.076). Having blood glucose levels in the upper quartile range (> or =8.8 mmol/L) on postoperative day 1 was independently associated with death (OR: 10.16, P=0.0002), infectious complications (OR: 1.76, P=0.04) and prolonged ICU stay (OR: 3.10, P<0.0001). Patients presenting with three or more hypoglycaemic episodes (<4.1 mmol/L) had increased rates of mortality (OR: 9.08, P<0.0001) and complications (OR: 8.57, P<0.0001). CONCLUSION: Glucose levels greater than 8.8 mmol/L on postoperative day 1 and having three or more hypoglycaemic episodes in the postoperative period were predictive of mortality and morbidity among patients undergoing cardiovascular surgery. This suggests that a multidisciplinary approach may be able to achieve better postoperative blood glucose control. Conclusion: Objectif: L'hyperglycémie a été reconnue comme facteur prédictif de morbidité et mortalité après un pontage aortocoronaire. Notre étude avait pour objectif d'évaluer la prise en charge postopératoire des glycémies chez les patients qui avaient subi une intervention chirurgicale cardiovasculaire et d'évaluer l'impact de ces glycémies sur la mortalité et la morbidité intrahospitalières. Méthodes: Étude rétrospective recherchant une association entre la glycémie postopératoire et les complications postchirurgicales, la mortalité et la durée du séjour aux soins intensifs et à l'hôpital. Résultats: L'étude a été réalisée sur 642 patients qui avaient subi une intervention chirurgicale cardiovasculaire (ex. pontage aortocoronaire, endartérectomie de la carotide, pontage artériel des membres inférieurs). L'âge moyen est de 68 ± 10 ans et 74 % des patients étaient de sexe masculin. La mortalité intrahospitalière a été de 5 % parmi les patients diabétiques et 2 % chez les non-diabétiques (OR 1,66, p = 0,076). Les taux de glycémies situés dans le quartile supérieur (≥ 8,8 mmol/l) à j1 postopératoire sont associés de manière indépendante avec la mortalité (OR 10,16, 95 % CI 3,20-39,00, p = 0,0002), les complications infectieuses (OR 1,76, 95 % CI 1,02-3,00, p = 0,04) et la durée du séjour aux soins intensifs (OR 3,10, 95 % CI 1,83-5,38, p < 0,0001). Les patients qui avaient présenté trois hypoglycémies ou plus (< 4,1 mmol/l) ont présenté un taux augmenté de mortalité (OR 9,08, p ≤ 0,0001) et de complications (OR 8,57, p < 0,0001). Conclusion : Des glycémies supérieures à 8,8 mmol/l à j1 postopératoire et la présence de trois hypoglycémies ou plus en période postopératoire sont des facteurs prédictifs de mauvais pronostic chez les patients qui avaient subi une intervention chirurgicale cardiovasculaire. Ainsi, une approche multidisciplinaire devrait être proposée afin d'obtenir un meilleur contrôle postopératoire des glycémies.

Preliminary Experience in Treatment of Papillary and Macular Retinoblastoma: Evaluation of Local Control and Local Complications After Treatment with Linear Accelerator-Based Stereotactic Radiotherapy with Micromultileaf Collimator as Second-Line or Salvage Treatment after chemotherapy.

PURPOSE: To determine the local control and complication rates for children with papillary and/or macular retinoblastoma progressing after chemotherapy and undergoing stereotactic radiotherapy (SRT) with a micromultileaf collimator. METHODS AND MATERIALS: Between 2004 and 2008, 11 children (15 eyes) with macular and/or papillary retinoblastoma were treated with SRT. The mean age was 19 months (range, 2-111). Of the 15 eyes, 7, 6, and 2 were classified as International Classification of Intraocular Retinoblastoma Group B, C, and E, respectively. The delivered dose of SRT was 50.4 Gy in 28 fractions using a dedicated micromultileaf collimator linear accelerator. RESULTS: The median follow-up was 20 months (range, 13-39). Local control was achieved in 13 eyes (87%). The actuarial 1- and 2-year local control rates were both 82%. SRT was well tolerated. Late adverse events were reported in 4 patients. Of the 4 patients, 2 had developed focal microangiopathy 20 months after SRT; 1 had developed a transient recurrence of retinal detachment; and 1 had developed bilateral cataracts. No optic neuropathy was observed. CONCLUSIONS: Linear accelerator-based SRT for papillary and/or macular retinoblastoma in children resulted in excellent tumor control rates with acceptable toxicity. Additional research regarding SRT and its intrinsic organ-at-risk sparing capability is justified in the framework of prospective trials.

Multiple-scale hydrological and geophysical data integration through non-linear Bayesian sequential simulation

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Local Distance-Based Generalized Linear Models using the dbstats package for R

This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing. Distances between individuals are the only predictor information needed to fit these models. Therefore they are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. Models can be fitted and analysed with the R package dbstats, which implements several distancebased prediction methods.

The 245 kb amplified chromosome of Leishmania (V.) braziliensis contains a biopterin transporter gene

Leishmania (V.) braziliensis M2903 presents a small linear and stable 245 kb chromosome originating from a genomic amplification. Similar amplifications present in other species of Leishmania contain a gene coding for a biopterin transporter. Since Leishmania is auxotrophic for this metabolite, this amplification could result from the need to better capture biotpterin from growth media under specific circumstances. In this paper we show that this gene is also present in L. (V.) braziliensis small chromosome, which shares sequences with other genomic amplifications already described.

BlastR--fast and accurate database searches for non-coding RNAs.

We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.

Biased gene conversion and GC-content evolution in the coding sequences of reptiles and vertebrates.

Mammalian and avian genomes are characterized by a substantial spatial heterogeneity of GC-content, which is often interpreted as reflecting the effect of local GC-biased gene conversion (gBGC), a meiotic repair bias that favors G and C over A and T alleles in high-recombining genomic regions. Surprisingly, the first fully sequenced nonavian sauropsid (i.e., reptile), the green anole Anolis carolinensis, revealed a highly homogeneous genomic GC-content landscape, suggesting the possibility that gBGC might not be at work in this lineage. Here, we analyze GC-content evolution at third-codon positions (GC3) in 44 vertebrates species, including eight newly sequenced transcriptomes, with a specific focus on nonavian sauropsids. We report that reptiles, including the green anole, have a genome-wide distribution of GC3 similar to that of mammals and birds, and we infer a strong GC3-heterogeneity to be already present in the tetrapod ancestor. We further show that the dynamic of coding sequence GC-content is largely governed by karyotypic features in vertebrates, notably in the green anole, in agreement with the gBGC hypothesis. The discrepancy between third-codon positions and noncoding DNA regarding GC-content dynamics in the green anole could not be explained by the activity of transposable elements or selection on codon usage. This analysis highlights the unique value of third-codon positions as an insertion/deletion-free marker of nucleotide substitution biases that ultimately affect the evolution of proteins.

Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.